Longitudinal Data Analysis

! Please note that on Tuesday (and only on Tuesday) the registration for the workshops and the conference will not take place in the ZiF but in the X-building of the university (see plan).

 

8:30     The conference and workshop registration begins at 8:30 in room X-D2-204 (X= X-building, D2= second floor in D-section, 204= room number).

 

Pre-Conference Workshops:

 

9:30-13:00 and 14:00-17:00

Longitudinal Modeling and Missing Data Handling in Blimp

Room: X-C3-107

Craig Enders

Missing data are a ubiquitous feature of nearly all longitudinal modeling applications, arising through participant non-response, attrition, and sometimes even by design. Failure to account appropriately for missing values when conducting statistical analyses can result in badly biased estimates and incorrect inferences about the relationships under study. Longitudinal Modeling and Missing Data Handling with Blimp is a full-day workshop focused on Bayesian estimation and multiple imputation, as implemented in the Blimp software application. These procedures are advantageous because they use all available data and make realistic assumptions about the cause of missingness; estimates and significance tests are therefore valid in a broader range of situations than historical methods such as deleting incomplete data records. The purpose of this workshop is to provide participants with foundational knowledge about the application of Bayesian estimation and multiple imputation to longitudinal data analyses. To this end, the workshop will include a mix of theoretical information, practical tips, and computer demonstrations involving real world data sets. A review of mixed (multilevel) models for longitudinal data will be provided, but familiarity with this topic will be beneficial. Workshop topics are listed below.

 

9:30-13:00 and 14:00-17:00

Latent State-Trait Modeling with Mplus

Room: X-D2-103

Christian Geiser

In this applied workshop, Christian Geiser provides an introduction to latent state-trait modeling in the Mplus software. The workshop covers basic and advanced models and methods of longitudinal confirmatory factor analysis. We will discuss longitudinal measurement invariance testing and analyze models for separating trait, state residual, method, and measurement error components. Participants can bring their own laptop with the demo version of Mplus to follow the data examples